Abstract: Radar super-resolution imaging methods with joint low-rank and sparse constraints have garnered increasing attention. However, in complex imaging scenarios, the low-rank property of the ...

Numerical-Methods-Project/ │ ├── README.md │ ├── 01_Solution_of_Linear_Equations/ │ │ │ ├── Gauss_Elimination/ │ │ ├── theory.md ...

Kernel ridge regression (KRR) is a regression technique for predicting a single numeric value and can deliver high accuracy for complex, non-linear data. KRR combines a kernel function (most commonly ...

Accurate spectral analysis of high-energy astrophysical sources often relies on comparing observed data to incident spectral models convolved with the instrument response. However, for gamma-ray ...

ABSTRACT: Attrition is a common challenge in statistical analysis for longitudinal or multi-stage cross-sectional studies. While strategies to reduce attrition should ideally be implemented during the ...

One of the ironies of the moment we’re in is that this inversion of good and evil, truth and falsehood has become more widespread and extreme at the very time that science, technology, and ...

Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most difficult tasks in numerical ...

Matrix factorization techniques, such as principal component analysis (PCA) and independent component analysis (ICA), are widely used to extract geological processes from geochemical data. However, ...

1 Ministère du Pétrole, Immeuble Ex-ONAREM, Niamey, République du Niger. 2 The World Bank, ACE-CEFOR, University of Port Harcourt, Port Harcourt, Nigeria. 3 ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Satellite data provides essential insights into the spatiotemporal distribution of CO ...